要防止本地文件上传到BigQuery，可以使用以下解决方法：

1. 使用BigQuery API进行数据导入：使用BigQuery API可以直接将数据从本地上传到BigQuery，而不需要将文件上传到云端。

from google.cloud import bigquery

def upload_local_file_to_bigquery(dataset_id, table_id, file_path):
    client = bigquery.Client()
    dataset_ref = client.dataset(dataset_id)
    table_ref = dataset_ref.table(table_id)

    job_config = bigquery.LoadJobConfig()
    job_config.source_format = bigquery.SourceFormat.CSV

    with open(file_path, "rb") as source_file:
        job = client.load_table_from_file(source_file, table_ref, job_config=job_config)

    job.result()  # Wait for the job to complete

    print("File uploaded to BigQuery.")

# 示例用法
dataset_id = "your-dataset-id"
table_id = "your-table-id"
file_path = "path/to/local/file.csv"
upload_local_file_to_bigquery(dataset_id, table_id, file_path)

2. 使用云存储进行数据导入：将本地文件上传到云存储（如Google Cloud Storage）中，然后使用BigQuery的外部表功能从云存储中读取数据。

from google.cloud import bigquery

def import_data_from_cloud_storage(dataset_id, table_id, bucket_name, file_path):
    client = bigquery.Client()
    dataset_ref = client.dataset(dataset_id)
    table_ref = dataset_ref.table(table_id)

    external_config = bigquery.ExternalConfig("CSV")
    external_config.source_uris = ["gs://{}/{}".format(bucket_name, file_path)]
    external_config.options.skip_leading_rows = 1

    table = bigquery.Table(table_ref, schema=schema)
    table.external_data_configuration = external_config

    client.create_table(table)

    print("Data imported from Cloud Storage.")

# 示例用法
dataset_id = "your-dataset-id"
table_id = "your-table-id"
bucket_name = "your-bucket-name"
file_path = "path/to/file.csv"
import_data_from_cloud_storage(dataset_id, table_id, bucket_name, file_path)

这些方法都可以避免直接上传本地文件到BigQuery，从而提高数据的安全性和可控性。